⚡ Bolt: Cache redundant matrix inversions in vuongtest.R

[seonghobae]

💡 What: Extracted redundant chol2inv(chol(AB1$A)) and chol2inv(chol(AB2$A)) computations into variables invA1 and invA2 in the calcLambda function within R/vuongtest.R.

🎯 Why: Formulaic translation of math equations into code often results in repeated identical calculations. In this case, matrix inversions (an $O(n^3)$ operation) were computed twice for each block matrix component.

📊 Impact: Reduces matrix inversions in the calcLambda step by 50% (from 4 down to 2 operations), which will significantly improve execution time for comparisons involving models with many parameters or very large covariance matrices.

🔬 Measurement: Verify by running the vuongtest() function on two nested models with large parameter spaces and measuring execution time with and without the patch. The optimization is mathematically equivalent and verified to be safe.

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PR created automatically by Jules for task 4387574010166644118 started by @seonghobae

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[Copilot]

Pull request overview

This PR optimizes calcLambda() in R/vuongtest.R by caching repeated chol2inv(chol(A)) computations into intermediate variables, reducing redundant matrix inversions during Vuong test calculations (notably beneficial for large covariance matrices / parameter counts).

Changes:

• Cache chol2inv(chol(AB1$A)) and chol2inv(chol(AB2$A)) into invA1 / invA2 and reuse them when building W.
• Add an internal .jules/bolt.md note documenting the optimization pattern (avoid redundant inversions in formulaic translations).

Reviewed changes

Copilot reviewed 2 out of 2 changed files in this pull request and generated no comments.

File	Description
R/vuongtest.R	Avoids duplicate matrix inversions in calcLambda() by reusing cached invA1/invA2 when constructing W.
.jules/bolt.md	Documents the general performance lesson and action item for future similar optimizations.

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